Introduction to dbt for Data Transformation and Analytics Engineering

Modern data teams face a common challenge: managing complex SQL pipelines without losing track of code quality, documentation, and testing. This course introduces you to dbt (data build tool), the industry-standard utility that bridges the gap between raw data transformation and software engineering best practices. You will transition from writing disorganized SQL scripts to building maintainable, version-controlled analytics pipelines. Through clear text explanations and structured code examples, you will learn how to organize your data transformation logic efficiently. What you'll learn: - Understand the core architecture of dbt and its role in the modern data stack - Write modular, reusable data models using SQL and Jinja templating - Configure automated tests to ensure data quality and schema consistency - Generate and maintain interactive documentation and data lineage graphs - Apply version control and CI/CD fundamentals to your data engineering workflows This course starts with foundational concepts, defining key terminology and explaining how dbt fits into modern data warehouses. You will then progress through step-by-step written guides covering model creation, testing strategies, and deployment basics. This course is designed for beginner data analysts, database administrators, and aspiring analytics engineers. No prior experience with dbt is required, though a basic understanding of SQL is helpful. Start reading today to transform your SQL workflows into professional analytics engineering pipelines.